Share this article on:

Health Care System Measures to Advance Preconception Wellness: Consensus Recommendations of the Clinical Workgroup of the National Preconception Health and Health Care Initiative

Frayne, Daniel J. MD; Verbiest, Sarah DrPH, MSW; Chelmow, David MD; Clarke, Heather CNM, DNP; Dunlop, Anne MD; Hosmer, Jennifer MD, MPH; Menard, M. Kathryn MD, MPH; Moos, Merry-K. BSN, MPH; Ramos, Diana MD, MPH; Stuebe, Alison MD, MSc; Zephyrin, Laurie MD, MPH

doi: 10.1097/AOG.0000000000001379
Contents: Consensus Statement

Preconception wellness reflects a woman's overall health before conception as a strategy to affect health outcomes for the woman, the fetus, and the infant. Preconception wellness is challenging to measure because it attempts to capture health status before a pregnancy, which may be affected by many different service points within a health care system. The Clinical Workgroup of the National Preconception Health and Health Care Initiative proposes nine core measures that can be assessed at initiation of prenatal care to index a woman's preconception wellness. A two-stage web-based modified Delphi survey and a face-to-face meeting of key opinion leaders in women's reproductive health resulted in identifying seven criteria used to determine the core measures. The Workgroup reached unanimous agreement on an aggregate of nine preconception wellness measures to serve as a surrogate but feasible assessment of quality preconception care within the larger health community. These include indicators for: 1) pregnancy intention, 2) access to care, 3) preconception multivitamin with folic acid use, 4) tobacco avoidance, 5) absence of uncontrolled depression, 6) healthy weight, 7) absence of sexually transmitted infections, 8) optimal glycemic control in women with pregestational diabetes, and 9) teratogenic medication avoidance. The focus of the proposed measures is to quantify the effect of health care systems on advancing preconception wellness. The Workgroup recommends that health care systems adopt these nine preconception wellness measures as a metric to monitor performance of preconception care practice. Over time, monitoring these baseline measures will establish benchmarks and allow for comparison within and among regions, health care systems, and communities to drive improvements.

Supplemental Digital Content is Available in the Text.The National Preconception Health and Healthcare Initiative recommends that health care systems adopt nine preconception wellness measures to drive improvements in birth outcomes.

Corresponding author: Daniel J. Frayne, MD, 123 Hendersonville Road, Asheville, NC 28803; e-mail: dan.frayne@mahec.net.

Financial Disclosure The authors did not report any potential conflicts of interest.

For a list of Consensus Panel Members and their affiliations, see Appendix 1 online at http://links.lww.com/AOG/A792.

Funding for the consensus meeting received through the W. K. Kellogg Foundation.

The authors thank the members of the Clinical Workgroup Consensus Panel for their time and expertise in development of these recommendations, the W. K. Kellogg Foundation for financial support of the in-person meeting, and Suzanne Yergenson for manuscript assistance.

The National Preconception Health and Healthcare Initiative, a public–private partnership, advances evidence, strategies, and innovations for improving women's wellness and reducing infant mortality through the promotion of preconception health. Initiated by the Centers for Disease Control and Prevention in 2003, representatives from federal, state, and local public health agencies along with clinicians and researchers have combined resources and worked together voluntarily to develop and implement recommendations for improving preconception health and care in the United States.1 After a series of strategic plans over the years, domains for action have included policy, population health indicators, consumer outreach and message development, research, public health programming, clinician education, and evidence-gathering.2 Although progress has been made on many fronts, clinical implementation has lagged, hampered by a lack of consensus measures to track quality of preconception care. To address this gap, we propose a set of outcome and process measures to track preconception wellness in health care systems.

Back to Top | Article Outline

BACKGROUND

Despite ranking first in the world for health care spending, the United States ranks 26th in infant mortality and is the only developed country where maternal mortality and severe morbidity are on the rise, especially among minority women.3–5 These trends persist despite advances in perinatal care.6 To change this trajectory, it is essential to improve the health status of women before pregnancy. Rising rates of chronic conditions, including obesity, hypertension, diabetes, and substance use, have been linked to rising rates of maternal mortality and severe morbidity.7 These chronic conditions also contribute to high infant mortality rates, principally as a result of preterm births.8–10 In addition, women are waiting longer to become pregnant, resulting in more first births among women ages 35 years or older.11 Increased maternal age carries increased health risks to both the mother and infant.12 To improve health outcomes for mothers and their infants, we must address women's medical conditions, risks, and health behaviors before pregnancy.1,13

To drive systems changes that can improve perinatal outcomes, we propose a set of preconception wellness metrics. Efforts to implement comprehensive approaches to women's health and wellness are particularly timely given changes in access to care and coverage of preventive services occurring with implementation of the Affordable Care Act.14,15 Under this federal act, the U.S. health care system is transforming service financing and delivery, aiming to improve quality of care and population health while reducing per-capita costs. The finance reforms involve shifting from volume- to value-driven reimbursement based on meaningful outcome measurements and incentivizing high-quality, cost-effective care. Delivery reforms include shifting from episodic care management to collaborative care that involves integration that is horizontal, vertical, and coordinated.

To ensure that these reforms support optimal preconception health, we need metrics for preconception health care delivery. Because most pregnancies are unplanned, these measures must assess care provided to all women—those actively desiring pregnancy and those who become pregnant unintentionally. Measuring preconception health care delivery is challenging given the scope of preconception care and the breadth of domains that affect a woman's preconception health (eg, clinical factors, social determinants of health, mental wellness, and access to care). As a result, health care systems are unsure what to measure to assess current care and drive improvement or what sectors should be held accountable for preconception health care delivery.

We propose an initial composite of nine measures that, if fully addressed through risk modification, should improve women's, fetal and infant health outcomes as described in the 2008 Supplement on the Clinical Content of Preconception Care in the American Journal of Obstetrics and Gynecology.16 These proposed measures are fundamentally an index of health care system performance rather than of individual clinicians or practices, reflecting that multiple health care providers, clinics, and public health programs deliver preconception care. In addition to measuring the health care system's delivery of preconception care, these measures can quantify prevalent preconception health issues for a community or subset of the population. We anticipate that these measures will provide critical data to inform both individual and system approaches to improving preconception health care delivery, ultimately improving women's health and reducing maternal and infant morbidity and mortality.

The importance of and procedures for preconception care are well described.16,17 Health care providers of clinical care have the evidence needed to guide preconception care, yet this care is not being provided or documented in a way that will achieve desired outcomes. As Stanford and Hobbins note, “It's not a question of whether you provide preconception care, rather it's a question of what kind of preconception care you are providing.”18 Health care systems have recognized that measuring quality drives improvement. There are many accepted quality measures from a variety of institutions around chronic disease management, preventive services delivery, access to care, patient satisfaction, and guideline adherence. A review of measures through groups such as Healthcare Effectiveness Data and Information Set, National Center for Quality Assurance, National Quality Forum, Patient Centered Medical Home, Patient Quality Reporting System, Health and Human Service Administration's Uniform Data System, Accountable Care Organizations, and electronic health records meaningful use criteria highlight multiple opportunities for benchmarking distinct well woman services, which, in many cases, are also measures of preconception wellness. Healthy women have healthier pregnancy outcomes.

A woman's level of well-being at the time of conception reflects her preconception wellness. Preconception wellness should be distinguished from preconception care. Women's wellness reflects a woman's overall health as influenced by her clinical and psychosocial status and her environment at any point in time. Preconception wellness is a state of being, whereas preconception care is a set of interventions aimed at achieving this state of wellness.

Although components of preconception wellness are included in many current national and system-based quality measures, risks specific to pregnancy are not addressed. In fact, some existing quality measures conflict with preconception wellness targets. For example, a diabetes quality measure is percent of patients with hemoglobin A1c greater than 9%, which far exceeds the goal of less than 6.5% for women at risk of pregnancy to minimize the risk of congenital malformations.19–21 Additionally, angiotensin-converting enzyme (ACE) inhibitors and statins are standard of care for ideal control of hypertension, renal protection, and cardiovascular risk reduction in diabetes; however, as a result of their teratogenic potential, they should be avoided in the earliest weeks of pregnancy, often before prenatal care has begun. For a practice caring for women with diabetes, achieving current wellness measures for hemoglobin A1c, ACE inhibitor, and statin use could inadvertently increase risk for adverse pregnancy outcomes.

The purpose of preconception care is to optimize each woman's health before pregnancy to decrease risks during pregnancy and improve birth outcomes; thus, an intermediate outcome of preconception care is the state of a woman's health at the time she becomes pregnant—her “preconception wellness.” As such, we propose that preconception wellness be measured at completion of the initial prenatal assessment for several reasons: 1) measurement at the initial assessment minimizes the bias in pregnancies that are detected, given that not all pregnancies end in a birth (miscarriage, termination, or fetal loss); 2) the first prenatal assessment is where the effect of preconception wellness is most recognized; and 3) many of the proposed measures are already collected as standard care at this assessment, minimizing the effect on clinical workflow. Although earlier time points (eg, before pregnancy) would be more inclusive and better reflections of women's wellness, the Workgroup felt that this would not be feasible, because many women do not enter the health care system until pregnancy, and access to care remains limited in the United States.22

Back to Top | Article Outline

METHODS

The Clinical Workgroup of the National Preconception Health and Health Care Initiative was first convened in 2006 with clinicians recruited to represent different areas of expertise and professional organizations, including family medicine, obstetrics and gynecology, maternal–fetal medicine, nurse midwifery, nursing, and public health. Typically meeting approximately four times a year, the Workgroup amplified their efforts between November 2014 and April 2015 to develop the measures reported in this article. A two-stage web-based Delphi survey and a face-to-face meeting of key opinion leaders of the Clinical Workgroup were used to develop consensus for a framework to measure preconception wellness.23 Measures subjected to the Delphi survey were identified by systematic literature review and stakeholder feedback. Reviewers informally ranked the importance of the measures based on the ease of implementation and evidence to affecting improvement. During this time the group met five times along with three segments of meeting preparation work and one segment of postmeeting work. Consensus panel members provided feedback between survey stages. Through iterative literature review and discussion, members reached full consensus around surrogate preconception care measures that reflect the receipt of quality care from the health care system and their ability to affect maternal and child health outcomes. Steps to reach consensus included: 1) defining preconception care compared with preconception wellness or health, 2) determining when to measure quality preconception care and wellness, 2) reviewing evidence for all potential measures, 4) assigning value and feasibility to each measure, 5) achieving consensus on a minimal core set of preconception wellness measures, and 6) assessing whether this core set of measures could be prioritized.

More than 20 preconception wellness measures were considered for inclusion. The criteria used in assessing the potential preconception wellness measures are shown in Box 1. A matrix was created to grade each potential measure as high, medium, or low value in its congruency with currently accepted quality measures, ease of extraction of reliable data from electronic health records, the evidence available for reducing identified risks, effect on pregnancy outcomes (for both women and infants), and ability to affect change within the health care system. Current quality measures from national reporting groups were crosswalked with preconception care components to determine what might already be captured as discrete data. The panel discussed each potential measure until it had reached complete consensus. Our goal was to define the smallest number of metrics that would capture the greatest proportion of a woman's preconception wellness.

Back to Top | Article Outline

Box 1 Criteria for Preconception Health Wellness Measures Cited Here...

  • An evidence-based recommendation for ameliorating risk in the preconception period exists (strength of relationship between the measure and poor maternal and child health outcomes)
  • Condition is prevalent (percentage of women of reproductive age who are affected or degree of risk associated with poor maternal and child health outcomes)
  • Can be assessed by measure that is a component of standard prenatal care
  • Reported as a quality measure for major organization (eg, NQF, HEDIS, ACO, UDS) (high=exact measure exists; medium=similar measure exists, some modification required; low=no measure currently exists)
  • Can be easily collected or extracted from medical record (high=commonly collected in discrete EHR field; medium=could be incorporated into EHR discrete field although not commonly done currently; low=difficult to create an EHR workflow for collection)
  • Data source is considered valid (high=not up to human interpretation; medium=some variability in collecting and reporting may exist; low=high variability in reporting and collecting may exist)
  • Data source is considered reliable (high=data extracted from computerized data set, eg, laboratory value, vital sign, evidence-based screen response, date; medium=patient report using a standardized questionnaire, eg, medication use, pregnancy intention; low=inferred data or patient reports, which often are unreliable, eg, alcohol use before pregnancy, substance use)

NQF, National Quality Forum; HEDIS, Healthcare Effectiveness Data and Information Set; ACO, Accountable Care Organization; UDS, Uniform Data System; EHR, electronic health record.

Back to Top | Article Outline

CONSENSUS RECOMMENDATION: PRECONCEPTION WELLNESS MEASURES

Nine measures met consensus group criteria for value and feasibility to index a woman's preconception wellness on entering pregnancy. Table 1 displays the recommended measures with suggested data sources and target values along with a crosswalk with existing national quality measures. A woman who met all these targets at her initial prenatal assessment would be considered to have a high degree of preconception wellness. Subsequently, we summarize the evidence and value for improving birth outcomes, the ease of collection and extraction, standard of care and reliability of data, and the rationale for each measure. Of note, several measures assess control of existing health conditions such as diabetes or depression; the intention of these measures is to quantify the extent to which women with chronic health conditions have achieved optimal control before conception, not to suggest that women with these health conditions should not get pregnant.

Table 1-a

Table 1-a

Table 1-b

Table 1-b

Back to Top | Article Outline

MEASURE RATIONALE

  1. Pregnancy intention (evidence and value: high; ease and reliability: medium). Unintended pregnancy is a risk factor for adverse birth outcomes and a key indicator for access to and use of reproductive health care. Currently, more than 50% of pregnancies in the United States are unintended (mistimed or unwanted).24,25 This measure affects all women. It is not a currently reported quality measure. A validated measure of pregnancy planning and intention, the London Measure of Unplanned Pregnancy, has been proposed.26
  2. Access to care (evidence and value: high; ease and reliability: high). Initiating prenatal care in the first trimester is a key measure of health care access and improves birth outcomes by allowing early risk assessment such as anomaly screening and implementation of evidence-based interventions to prevent adverse outcomes. It also may be a marker of a woman's connection to a health care system. This measure affects all women. It is a core quality measure for federally qualified community health centers.27,28
  3. Multivitamin with folic acid use before conception (evidence and value: high; ease and reliability: medium). Preconception folic acid supplementation is associated with a 70% reduction in neural tube defects.29 Including a multivitamin with folate has additional benefits in birth outcomes.30 However, this benefit is primarily seen if the multivitamin with folate is consumed before conception. Most women take a prenatal vitamin during pregnancy but currently less than one third of women take or are even aware of the importance of preconception folate.31 This measure affects all women. It is not a currently reported quality measure, although an accurate medication list including over-the-counter medications is a part of Patient Quality Reporting System meaningful use standards.32
  4. Tobacco avoidance at the time of first prenatal assessment (evidence and value: high; ease and reliability: high). Tobacco is well known to be one of the most important contributing risk factors in cardiovascular disease, stroke, and certain cancers.33 Smoking cessation before or during pregnancy decreases risks for preterm birth, hypertensive disorders, intrauterine growth restriction, and low birth weight. This measure affects all women who currently use tobacco (18.7% of U.S. women 18–44 years of age).31 The preferred method of screening is use of a structured question format (such as the 5 As), which has been validated against biochemical screens (such as cotinine testing) and superior to a “yes or no” approach.34 Documentation of tobacco use is a current quality measure for most organizations.
  5. Absence of uncontrolled depression at the first prenatal assessment (evidence and value: high; ease and reliability: high). Mental health issues are common among women of reproductive age.31,35 Stress, anxiety, depression, or other poor states of emotional health are associated with increased pregnancy risks and affect the well-being of future children. Women who are depressed are more likely to have an unintended pregnancy, and women who are depressed during pregnancy have worse birth outcomes.36–38 Screening with the Patient Health Questionaire-9 or other instrument could serve as a marker of mental health issues. A woman with current depression that is adequately treated and controlled should have a negative screen. Universal depression screening is the standard of care and important for all women. Depression screening is a current quality measure for most organizations.
  6. Healthy weight (normal body mass index [BMI, calculated as weight (kg)/[height (m)]2]) at the first prenatal assessment (evidence and value: high; ease and reliability: high). A prepregnancy BMI of greater than 30 or less than 18 increases perinatal morbidity including preterm birth, preeclampsia, spontaneous abortion, and stillbirth.39 It is a major contributor to severe maternal morbidity and mortality.40 Measuring BMI and determining Institute of Medicine-recommended weight gain goals during pregnancy is standard care. This measure is important for all women. Assessment of BMI is a current quality measure for most organizations.
  7. Absence of sexually transmitted infections at the first prenatal assessment (evidence and value: high; ease and reliability: high). Active sexually transmitted infections during pregnancy increase perinatal risks.41 The Centers for Disease Control and Prevention has clear guidelines for screening and all pregnant women should be routinely screened for human immunodeficiency virus, syphilis, and hepatitis B and selectively screened based on risk factors for gonorrhea, chlamydia, and hepatitis C.42 A woman with adequate access to health care ideally would be screened and treated or optimally managed before pregnancy. This measure is important for all women at risk of infection. Currently, data are reported for chlamydia, hepatitis B, and human immunodeficiency virus screening in selected risk groups.
  8. Optimal glycemic control in women with pregestational diabetes at the time of first prenatal assessment (evidence and value: high; ease and reliability: high). The prevalence of pregestational diabetes is approximately 3%.31 Poorly controlled diabetes is strongly associated with increased maternal and fetal risks. Improved glycemic control can significantly decrease these risks.19–21 This measure is important for all women with a risk for or diagnosis of diabetes. Reporting hemoglobin A1c values for patients with diabetes is a current quality measure for most organizations.
  9. Teratogenic medication avoidance before conception (evidence and value: high; ease and reliability: medium). A growing number of women of reproductive age are treated for chronic disease—eg, diabetes, hypertension, chronic pain, depression, hypercoagulable states, and seizure disorders.43 Dunlop et al44 report, “It is estimated that approximately 10–15% of congenital anomalies are due to teratogenic maternal exposures to medications, alcohol, or other exogenous factors that have adverse effects on the developing embryo or fetus.” Recent studies have found that in the first trimester, 80% women take at least one prescription or over-the-counter medication45 and 7.5% take four or more medications.46 Many commonly prescribed medications are both teratogenic and chronic disease quality measures. For example, ACE inhibitor and statin use as quality measures for patients with diabetes does not consider pregnancy intention. With optimal preconception care, women treated with teratogenic medications would discuss pregnancy intentions with their health care providers; health care providers would ensure that women not desiring pregnancy utilized effective contraception and women planning to conceive would be counseled on the risks and benefits of potential alternative treatment regimens. If such optimal care were provided, teratogenic medication use in the first trimester would be limited to women without effective therapeutic alternatives. Although there are many teratogenic medications, a few of the most common are ACE inhibitors, angiotensin receptor blockers, statins, lithium, valproic acid, and warfarin.44 It is not a currently reported quality measure, although an accurate medication list including over-the-counter medications is a part of Patient Quality Reporting System meaningful use standards.
Back to Top | Article Outline

DISCUSSION

The Workgroup debated whether these measures could be prioritized or ranked. Of particular interest was the primacy of pregnancy intention. However, taken alone, even this measure would not adequately describe preconception wellness. For example, a woman could plan a pregnancy, yet not be taking folic acid supplementation, be a current smoker, have an active sexually transmitted infection, be unknowingly taking a teratogenic medication, and have inadequate glycemic control of her diabetes. This would not be considered entering pregnancy with a high degree of preconception wellness despite her pregnancy intention. No one measure taken in isolation is enough to describe preconception wellness, but, taken in aggregate, these nine measures adequately reflect a state of more optimal preconception health. By collecting and reporting on these measures, health care systems will be better informed as to the state of preconception wellness for the women they serve and be equipped to develop targeted strategies aimed at improving preconception care for a particular population or community.

A variety of additional measures were considered, including optimal blood pressure management in women with hypertension; optimal interpregnancy interval (greater than 18 months and less than 59 months); immunizations; alcohol use; substance use; interpersonal violence screening; stress screening; entering pregnancy understanding genetic risk; human immunodeficiency virus-positive women with low viral load threshold and receiving appropriate specialty care; anemia; maternal age; and human trafficking screens. Panelists also discussed the context within which health disparities are created and the effect of the social determinants of health on preconception health and birth outcomes. Although all of these areas are important to women's health and preconception wellness, they were excluded from the current list of recommendations, because they did not meet the previously described criteria. The group was challenged by the need to offer health care systems and clinicians a concise list of areas with the best evidence for risk modification. The nine measures chosen are in many ways linked to these other factors and thus could serve as surrogates for the wide array of risks affecting women of reproductive age.

Back to Top | Article Outline

SHARED ACCOUNTABILITY

The time has come to expand accountability for pregnancy outcomes and the health of the next generation. By measuring the state of preconception wellness, system leaders will identify issues needing attention in their particular community and be able to benchmark improvements. If women in a particular health care system are receiving their primary care or well woman care within the same clinic where they receive prenatal care, these measures can serve as an important metric of success. For women who receive their well woman care in other contexts, improving preconception wellness measures will require cross-clinic and multidisciplinary collaborations to enhance care delivery. These measures will also identify local priorities for preconception wellness, many of which will require community-wide partnerships. For example, high rates of unplanned pregnancy and lack of preconception folate use might prompt a health care system to focus on contraceptive access and folic acid education or distribution program as their main initiatives in the community. Conversely, high rates of teratogenic medication use and uncontrolled diabetes might prompt primary care and specialty clinician education around preconception risks in women with chronic disease and may lead to collaboration with care management teams and pharmacy initiatives in addition to direct to consumer education initiatives. In each case, both public and private health and community programs across all disciplines must promote preconception wellness. Everyone bears a portion of the responsibility for preconception wellness—from community health workers and home visitors to health educators, primary care providers, family planning providers, and specialists as well as hospital system administrators, payers, policymakers and, of course, women themselves.

Back to Top | Article Outline

CONCLUSIONS

The Preconception Health and Health Care Initiative Clinical Workgroup recommends that health care systems adopt these nine core preconception wellness measures. These measures will provide a metric to monitor performance of preconception care practice, thereby improving women's preconception wellness. Implementation will require modest but feasible changes in clinical workflow and electronic health record design to ensure that each measure is captured as a discrete data point by completion of the initial prenatal assessment. These steps will ensure that measure reports can be derived from the electronic health record. Baseline measures will inform quality improvement initiatives in primary care as well as community outreach and public health initiatives.

Over time, monitoring will establish benchmarks and allow for comparison within and among regions, health care systems, and communities to drive improvements. Implementing these quality measures and developing proven strategies to optimize wellness will require research at the health care system level. Funding organizations must prioritize research utilizing these measures so health care systems and communities can determine best practices for implementation, assess for key measurement outcomes and consequences, and develop interventions within communities that can improve preconception wellness. Although there is work ahead to operationalize these preconception wellness measures, we believe that the growing focus on providing quality well woman preventive care sets the stage for widespread adoption. The health of women of reproductive age is essential, both for women's own well-being and productivity as well as for that of future generations.

Back to Top | Article Outline

REFERENCES

1. Johnson K, Posner SF, Biermann J, Cordero JF, Atrash HK, Parker CS, et al.. Recommendations to improve preconception health and health care—United States. A report of the CDC/ATSDR Preconception Care Work Group and the Select Panel on Preconception Care. MMWR Morb Mortal Wkly Rep 2006;55:1–23.
2. Floyd RL, Johnson KA, Owens JR, Verbiest S, Moore CA, Boyle C. A national action plan for promoting preconception health and health care in the United States (2012–2014). J Womens Health (Larchmt) 2013;22:797–802.
3. MacDorman MF, Mathews TJ, Mohangoo AD, Zeitlin J. International comparisons of infant mortality and related factors: United States and Europe, 2010. In: National vital statistics reports. 2014;63. Available at: http://www.cdc.gov/nchs/data/nvsr/nvsr63/NVSR63_05.pdf. Retrieved October 5, 2015.
4. Kassebaum N, Bertozzi-Villa A, Coggeshall M, Shackelford KA, Steiner C, Heuton KR, et al.. Global, regional, and national levels and causes of maternal mortality during 1990–2013: a systematic analysis for the Global Burden of Disease Study 2013. Lancet 2014;384:980–1004.
5. Health expenditure per capita. In: Health at a glance 2013: OECD indicators, organisation for economic co-operation and development. Paris (France): OECD Publishing. Available at: http://dx.doi.org/10.1787/health_glance-2013-64-en. Retrieved November 21, 2013.
6. Mathews TJ, MacDorman MF. Infant mortality statistics from the 2004 period linked birth/infant death data set. National vital statistics reports. Hyattsville (MD): National Center for Health Statistics; 2007:55.
7. Barfield WD, Warner L. Preventing chronic disease in women of reproductive age: opportunities for health promotion and preventive services. Prev Chronic Dis 2012;9:E34.
8. Centers for Disease Control and Prevention. National vital statistics reports. Atlanta (GA): Centers for Disease Control and Prevention; 2012:60.
9. MacDorman MF, Callaghan WM, Mathews TJ, Hoyert DL, Kochanek KD. Trends in preterm-related infant mortality by race and ethnicity, United States, 1999–2004. Int J Health Serv 2007;37:635–41.
10. March of Dimes National Center for Health Statistics, fetal mortality data and period linked birth/infant death data. White Plains (NY): March of Dimes. Available at: www.marchofdimes.org/peristats. Retrieved February 8, 2015.
11. Mathews TJ, Hamilton BE. First births to older women continue to rise. NCHS data brief, no. 152. Hyattsville (MD): National Center for Health Statistics; 2014.
12. Creanga AA, Berg CJ, Syverson C, Seed K, Bruce FC, Callaghan WM. Pregnancy-related mortality in the United States, 2006–2010. Obstet Gynecol 2015;125:5–12.
13. Dunlop AL, Jack BW, Bottalico JN, Lu MC, James A, Shellhaas CS, et al.. The clinical content of preconception care: women with chronic conditions. Am J Obstet Gynecol 2008;199(suppl 2):S310–27.
14. Johnson K, Atrash H, Johnson A. Policy and finance for preconception care: opportunities for today and the future. Womens Health Issues 2008;18(suppl):S2–9.
15. Coverage of certain preventive services under the affordable care act. Fed Regist 2013;78.
16. Jack BW, Atrash H, Coonrad DV, Moos MK, O'Donnell J, Johnson K. The clinical content of preconception care: an overview and preparation of this supplement. Am J Obstet Gynecol 2008;199(suppl 2):S266–79.
17. Moos MK, Dunlop AL, Jack BW, Nelson L, Coonrod DV, Long R, et al.. Healthier women, healthier reproductive outcomes: recommendations for the routine care of all women of reproductive age. Am J Obstet Gynecol 2008;199(suppl 2):S280–9.
18. Ratcliffe SD, Baxley EG, Cline MK, Sakornbut EL. Family medicine obstetrics. Philadelphia (PA): Elsevier; 2008.
19. Guerin A, Nisenbaum R, Ray JG. Use of maternal GHb concentration to estimate the risk of congenital anomalies in the offspring of women with prepregnancy diabetes. Diabetes Care 2007;30:1920–5.
20. Pregestational diabetes mellitus. ACOG Practice Bulletin No. 60. American College of Obstetricians and Gynecologists. Obstet Gynecol 2005;105:675–85.
21. American Diabetes Association. Management of diabetes in pregnancy. Diabetes Care 2015;38(suppl 1):S77–9.
22. Salganicoff A, Ranji U, Wyn R. Women and health care. A national profile: key findings from the Kaiser Women's Health Survey. Menlo Park (CA): Kaiser Family Foundation; 2005. Available at: http://kaiserfamilyfoundation.files.wordpress.com/2013/01/women-and-health-care-a-national-profile-key-findings-from-the-kaiser-women-s-health-survey-chapter-6.pdf. Retrieved September 21, 2014.
23. Hsu CC, Sandford BA. The Delphi technique: making sense of consensus. Pract Asses Res Eval 2007;12:1–8.
24. Mosher WD, Jones J, Abma JC. Intended and unintended births in the United States: 1982–2010. National health statistics reports; no. 55. Hyattsville (MD): National Center for Health Statistics; 2012.
    25. Guttmacher Institute: unintended pregnancy in the US. New York (NY): Guttmacher Institute; 2015. Available at: http://www.guttmacher.org/pubs/FB-Unintended-Pregnancy-US.html. Retrieved October 5, 2015.
      26. Barrett G, Smith SC, Wellings K. Conceptualisation, development, and evaluation of a measure of unplanned pregnancy. J Epidemiol Community Health 2004;58:426–33.
      27. U.S. Department of Health and Human Services. Prenatal first trimester care access. U.S. Department of Health and Human Services. Available at: http://www.hrsa.gov/quality/toolbox/measures/prenatalfirsttrimester/. Retrieved October 15, 2015.
        28. U.S. Health Resources and Services Administration. 2014 Uniform Data System (UDS) Manual—December 31, 2014 vs. 1.1 OMB Number: 0915–0193, expiration date: 02/28/2018. Available at: http://bphc.hrsa.gov/datareporting/reporting/2014udsmanual.pdf. Retrieved Feb 4, 2015.
          29. Recommendations for the use of folic acid to reduce the number of cases of spina bifida and other neural tube defects. MMWR Morb Mortal Wkly Rep 1992;41:1–7.
            30. Wilson RD. Pre-conception folic acid and multivitamin supplementation for the primary and secondary prevention of neural tube defects and other folic acid-sensitive congenital anomalies [in English, French]. J Obstet Gynaecol Can 2015;37:534–52.
            31. Robbins CL, Zapata LB, Farr SL, Kroelinger CD, Morrow B, Ahluwalia I, et al.. Core state preconception health indicators—pregnancy risk assessment monitoring system and behavioral risk factor surveillance system, 2009. MMWR Surveill Summ 2014;63:1–62.
            32. Health Insurance Marketplace: Quality rating system measure technical specifications. Baltimore (MD): Centers for Medicare & Medicaid Services. Available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/QualityInitiativesGenInfo/Downloads/2016-QRS-Measure-Technical-Specifications.pdf. Retrieved September 2015.
              33. U.S. Department of Health and Human Services. The health consequences of smoking—50 years of progress: a report of the surgeon general. Atlanta (GA): U.S. Department of Health and Human Services, Centers for Disease Control and Prevention, National Center for Chronic Disease Prevention and Health Promotion, Office on Smoking and Health; 2014.
                34. Melvin CL, Dolan-Mullen P, Windsor RA, Whiteside HP Jr, Goldenberg RL. Recommended cessation counselling for pregnant women who smoke: a review of the evidence. Tob Control 2000;9(suppl 3):III80–4.
                35. Farr SL, Bitsko RH, Hayes DK, Dietz PM. Mental health and access to services among US women of reproductive age. Am J Obstet Gynecol 2010;203:542.e1–9.
                36. Reardon DC, Cougle JR. Depression and unintended pregnancy in the National Longitudinal Survey of Youth: a cohort study. BMJ 2002;324:151–2.
                37. Alder J, Fink F, Bitzer J, Hösli I, Holzgreve W. Depression and anxiety during pregnancy: a risk factor for obstetric, fetal and neonatal outcome? A critical review of the literature. J Matern Fetal Neonatal Med 2007;20:189–209.
                38. England MJ, Sim LJ, editors. Depression in parents, parenting and children: opportunities to improve identification, treatment, and prevention. Washington, DC: National Research Council; Institute of Medicine, Committee on Depression Parenting Practices, and the Healthy Development of Children, The National Academies Press; 2009.
                  39. Gardiner PM, Nelson L, Shellhaas CS, Dunlop AL, Long R, Andrist S, et al.. The clinical content of preconception care: nutrition and dietary supplements. Am J Obstet Gynecol 2008;199(suppl 2):S345–56.
                  40. Papachatzi E, Dimitriou G, Dimitropoulos K, Vantarakis A. Pre-pregnancy obesity: maternal, neonatal and childhood outcomes. J Neonatal Perinatal Med 2013;6:203–16.
                  41. Coonrod DV, Jack BW, Stubblefield PG, Hollier LM, Boggess KA, Cefalo R, et al.. The clinical content of preconception care: infectious disease in preconception care. Am J Obstet Gynecol 2008;199(suppl 2):S296–309.
                  42. Workowski KA, Berman S; Centers for Disease Control and Prevention (CDC). Sexually transmitted diseases treatment guidelines, 2010. MMWR Recomm Rep 2010;59:1–110.
                  43. Salganicoff A, Ranji U, Beamesderfer A, Kurani N. Women and healthcare in the early years of the affordable care act: key findings from the 2013 Kaiser women's health survey. Washington (DC): Kaiser Family Foundation; 2014.
                    44. Dunlop AL, Gardiner PM, Shellhaas CS, Menard MK, McDiarmid MA. The clinical content of preconception care: the use of medication and supplements among women of reproductive age. Am J Obstet Gynecol 2008;199(suppl 2):S367–72.
                    45. Thorpe PG, Gilboa SM, Hernandez-Diaz S, Lind J, Cragan JD, Briggs G, et al.. National Birth Defects Prevention Study. Medications in the first trimester of pregnancy: most common exposures and critical gaps in understanding fetal risk. Pharmacoepidemiol Drug Saf 2013;22:1013–8.
                    46. Mitchell AA, Gilboa SM, Werler MM, Kelley KE, Louik C, Hernández-Díaz S, et al.. Medication use during pregnancy, with particular focus on prescription drugs: 1976–2008. Am J Obstet Gynecol 2011;205:51.e1–8.
                    Figure

                    Figure

                    Supplemental Digital Content

                    Back to Top | Article Outline
                    © 2016 by The American College of Obstetricians and Gynecologists. Published by Wolters Kluwer Health, Inc. All rights reserved.